About NVIDIA

NVIDIA’s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.

In 2006, the creation of the CUDA programming model and Tesla GPU platform opened up the parallel-processing capabilities of the GPU to general-purpose computing. A powerful new approach to computing was born.

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NVIDIA Exerting Leadership in AI and Deep Learning

Deep Learning for Smart Cities: NVIDIA Metropolis is transforming the modern city.

Data is the lifeblood of the modern city. Today, it’s being captured by more than 500 million sensors worldwide, and that number is growing exponentially. Video represents one of the richest sensors used, generating massive streams of data that need analysis.

AI transforms how we capture, inspect, and analyze data to impact everything from traffic and parking management to law enforcement and city services. NVIDIA Metropolis is leading this AI revolution, giving you the tools, technologies, and expertise to meet every challenge with smarter, faster applications. It’s powered by proven NVIDIA technology—from NVIDIA® Tesla® in the data center and the cloud with NVIDIA Jetson™ at the edge.

Develop Smarter Solutions with NVIDIA DeepStream

The NVIDIA DeepStream SDK is ideal for developers who are creating and deploying AI-based solutions for video analytics applications at scale, offering a complete framework and all the essential building blocks. Applications of Intelligent Video Analytics (IVA) include understanding consumer behavior in retail, intelligent traffic systems, web content filtering, and ad injection.

DeepStream SDK offers the capability to gain rich insights through a heterogeneous concurrent neural network architecture. Developers can leverage multiple neural networks to process each video stream, giving them the flexibility to bring in different deep learning techniques to deliver more intelligent insights. DeepStream makes use of:

NVIDIA® TensorRT™ and NVIDIA CUDA® for AI and other GPU computing tasks.

To learn more about the full extent of NVIDIA DeepStream capabilities, review this blog.

Healthcare: Improving Patient Care with AI

Artificial Intelligence is transforming the world of medicine. AI can help doctors make faster, more accurate diagnoses. It can predict the risk of a disease in time to prevent it. It can help researchers understand how genetic variations lead to disease.

Mining Medical Data for Better, Quicker Treatment. Using GPU-accelerated deep learning to process and study a patient’s condition over time and to compare one patient against a larger population could help doctors provide better treatments.

Better, Faster Diagnoses. Medical images such as MRIs, CT scans, and X-rays are among the most important tools doctors use in diagnosing conditions ranging from spine injuries to heart disease to cancer. However, analyzing medical images can often be a difficult and time-consuming process.

Genomics for Personalized Medicine. Genomics data is accumulating in unprecedented quantities, giving scientists the ability to study how genetic factors such as mutations lead to disease. Deep learning could one day lead to what’s known as personalized or “precision” medicine, with treatments tailored to a patient’s genomic makeup.

Deep Learning to Aid Blind People. Nearly 300 million people worldwide struggle to manage such tasks as crossing the road, reading a product label, or identifying a face because they’re blind or visually impaired. Deep learning is beginning to change that.

Numerous other partnerships with academia allow NVIDIA working in unison with Advanced HPC to collaborate with leading researchers as well as build connections with professors and research facilities that are working to solve complex scientific challenges.

NVIDIA has reached tens of thousands of individuals seeking to extend their knowledge of AI into professional careers through the Deep Learning Institute (DLI). Offering free online courses and instructor-led workshops at conferences and onsite at businesses across the globe, the DLI provides remote and local access to education in deep learning and accelerated computing. DLI partnerships include an educator network that consists of experts from NVIDIA as well as the online educational providers Coursera and Udacity with its nanodegree programs.

Retail: AI from Supply Chain to Customer Sentiment

The landscape of traditional retail is experiencing a seismic shift. A rapidly evolving competitive environment, a global move towards digital shopping, and the ever-changing sentiments of highly informed buyers are forcing a new perspective in the industry. From this new perspective, we’re seeing the adoption of accelerated analytics, robotics, and deep learning.

The use of artificial intelligence in retail spans every aspect of the industry leading to the ever-increasing adoption of accelerated analytics, robotics, and deep learning. Whether your goal is to optimize your supply chain, use existing data to increase conversion, or customize shopping experiences with predictive modeling and micro-targeting/pricing, AI can help you meet your challenge.

Next-Gen Automation, Powered by Deep Learning

Today’s robots can learn, adapt, and evolve using capabilities like machine learning, computer vision, and navigation. NVIDIA® Jetson AGX™ systems uses the power of deep learning to drive this exciting new era of smart embedded robotics—from manufacturing and agriculture to security and home-based healthcare.

Robotics

The AI Factory, Powered by NVIDIA

AI-enabled smart factories are changing the way manufacturing is done. AI computing powers industrial robots, big data analytics, and IIOT-managing, analyzing, and acting on tremendous amounts of data from a variety of sensors. With solutions like NVIDIA® Jetson® at the edge or near-edge and NVIDIA® Tesla® in the cloud, smart factories are increasing efficiency, improving quality, and reducing setup costs.

Isaac SDK

In June of 2018, NVIDIA launched NVIDIA® Isaac™, a new platform to power the next generation of autonomous machines, bringing artificial intelligence capabilities to robotics. Isaac SDK makes it easy to add AI into robots for perception, navigation and manipulation. It also provides a framework to manage communications and transfer data within the robot architecture. To learn more about the broad capabilities of Isaac, review this press release of its launch.

Part of the SDK is Isaac Sim, a simulation environment for developing, testing and training autonomous machines in the virtual world. Engineering iterations and testing can be done in minutes and because the system is completely virtual, there’s no risk of damage or injury. Isaac Sim is fully integrated with the Isaac SDK, which enables hardware-in-the-loop testing with NVIDIA Jetson AGX Xavier.

Self-Driving Cars

Artificial Intelligence (AI) gives cars the ability to see, think, learn and navigate a nearly infinite range of driving scenarios. NVIDIA uses the power of AI and deep learning to deliver a breakthrough end-to-end solution for autonomous driving — from data collection, model training, and testing in simulation to the deployment of smart, safe, self-driving cars.

NVIDIA DRIVE Constellation™ is a data center solution that integrates powerful GPUs and DRIVE AGX Pegasus™. Advanced visualization software running on GPUs simulate cameras, radar, and lidar as inputs to DRIVE AGX Pegasus, which processes the data as if it were actually driving on the road. This scalable system is capable of generating billions of miles of diverse autonomous vehicle testing scenarios to validate hardware- and software-in-the-loop prior to deployment.

DRIVE Constellation and DRIVE Sim are coupled to create a digital feedback loop. Driving commands from Pegasus are sent in real-time to control the virtual vehicle traveling in the simulated environment and validate that the algorithms and software are operating correctly.

Dedicated Application AI Products

NVIDIA Jetson AGX Systems: The AI solution for autonomous machines.

Secure real-time Artificial Intelligence (AI) performance where you need it most with the high-performance, low-power NVIDIA Jetson AGX systems. Processing of complex data can now be done on-board edge devices. This means you can count on fast, accurate inference in everything from robots and drones to enterprise collaboration devices and intelligent cameras.

Jetson AGX Xavier.Jetson AGX Xavier is the world’s first computer expressly designed for robotics. With more than nine billion transistors, it delivers 32 deep learning TOPS (i.e., trillion operations per second). is the world’s leading platform for high-performance, energy-efficient AI computing. Robots need to be able to understand the world around them using a wide range of sensors. Jetson AGX Xavier enables this with six high-performance processing units—a 512-core NVIDIA Volta architecture Tensor Core GPU, an eight-core Carmel ARM64 CPU, a dual NVDLA deep learning accelerator, and image, vision, and video processors.

Jetson TX2 Module. This is an AI supercomputer on a module, powered by NVIDIA Pascal™ architecture. Best of all, it packs this performance into a small, power-efficient form factor that’s ideal for intelligent edge devices like robots, drones, smart cameras, and portable medical devices. Supports all the features of the Jetson TX1 module while enabling bigger, more complex deep neural networks.

More on NVIDIA and Autonomous Machines . . .

Autonomous machines learn, evolve, and react to the world around them with the power of AI. NVIDIA provides leading-edge solutions and support for a vast array of autonomous machines, including:

Drones & UAVs. An advanced new breed of drones uses deep learning and smart cameras to do everything from taking inventory in warehouses to leading search and rescue operations. To learn more, visit: NVIDIA Jetson Solutions for Drones & UAVs.

Industrial Robots. AI-powered industrial robots are ushering in a new era of automation, making factories safer and smarter and transforming manufacturing. To learn more, visit: NVIDIA Jetson AGX Systems for Robotics.

RAPIDS: NVIDIA GPU-Accelerated Data Science

Launched at GTC Europe (October, 2018), RAPIDS™ is a GPU-acceleration platform for data science and machine learning that enables even the largest companies to analyze massive amounts of data and make accurate business predictions at unprecedented speed. RAPIDS open-source software gives data scientists a giant performance boost as they address highly complex business challenges, such as predicting credit card fraud, forecasting retail inventory and understanding customer buying behavior.

To facilitate broad adoption, NVIDIA is integrating RAPIDS into Apache Spark, the leading open-source framework for analytics and data science. To obtain documentation and install information, click Rapids Documentation.

The NVIDIA AI inference platform delivers the performance, efficiency, and responsiveness critical to powering the next generation of AI products and services — in the cloud, in the data center, at the network’s edge, and in vehicles.

Unleash the Full Potential of NVIDIA GPUs with NVIDIA TensorRT. Using NVIDIA TensorRT, you can rapidly optimize, validate, and deploy trained neural networks for inference. TensorRT delivers up to 40X higher throughput in real-time latency when compared to CPU-only inference.

With support for every major framework, NVIDIA DRIVE continually grows smarter with over-the-air updates. Even after autonomous vehicles are in production, the platform accommodates new frameworks and models, enabling added capabilities and higher levels of autonomy.

Intelligent Video Analytics: A 2017 study released by LDV Capital projected that the total number of cameras in the world will reach nearly 45 billion. Those cameras are generating a massive amount of data every day. Deep learning is the best way to turn this raw video data into actionable insight, and GPU-based inference is the only way to do it in real time.

End-to-End GPU Inference for Smart Cities:NVIDIA Metropolis uses the low power of NVIDIA® Jetson™ in cameras and appliances at the edge, the massive compute of NVIDIA Tesla® servers in the cloud, and the NVIDIA DeepStream SDK powered by NVIDIA TensorRT™ to deliver a complete IVA solution.

AI for Embedded Devices: The NVIDIA Jetson platform offers the best throughput and performance per watt, the lowest latency, and the highest channel density, which translates into lower operating costs throughout a city’s network.

Embedded Devices: From portable medical devices to automated delivery drones, intelligent edge solutions demand advanced inference to solve complex problems. These devices need inference performance in a low-power, small form factor—onboard. The NVIDIA® Jetson™ platform delivers this performance in the world’s fastest, most power-efficient supercomputer for inference at the edge.

A Supercomputer on a Module for Autonomous Machines:NVIDIA Jetson TX2 is the latest addition to the industry-leading Jetson embedded platform. It’s based on NVIDIA’s Pascal architecture and is run at more than twice the power efficiency of its predecessor. This allows Jetson TX2 to run larger, deeper neural networks on edge devices; ensuring higher accuracy and faster response times for tasks like image classification, navigation, and speech recognition.

Robust Tools for Building AI Applications: The Jetson platform for AI at the edge is powered by NVIDIA GPU and supported by the NVIDIA JetPack SDK. The JetPack SDK includes NVIDIA TensorRT™ for optimizing deep learning models for inference and other libraries for AI, computer vision, and multimedia to take your ideas to production.

AI Across Industries: Jetson’s embeddable supercomputing capability gives developers the power to bring AI to applications that were once unimaginable. Blue River Technology, for example, is helping farmers grow more food with fewer chemicals. Blue River uses tractor-mounted, Jetson-powered smart cameras to identify crops and weeds in real time, and trigger precisely metered sprays that kill the weeds and nurture the lettuce.

CUDA

Led by famed researcher Ian Buck, NVIDIA launched CUDA® – the world’s first solution for general-computing on GPUs – in 2006. CUDA is a parallel computing platform and programming model enabling developers to dramatically accelerate computing applications by harnessing the power of GPUs. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions via basic keywords.

CUDA accelerates applications across a wide range of domains, including:

Data Center Products and Solutions

Accelerating Data Center Workloads with GPUs

From scientific discoveries to artificial intelligence, modern data centers are key to solving some of the world’s most important challenges. The NVIDIA Volta accelerated computing platform gives these data centers the power to accelerate both artificial intelligence and high performance computing workloads.

Data Center Products

NVIDIA® Tesla®

NVIDIA HGX-2

NVIDIA GPU Cloud

NVIDIA® Tesla®: The world’s leading platform for the accelerated data center

Accelerating scientific discovery, visualizing big data for insights, and providing smart AI-based services to the enterprise are everyday challenges for researchers and engineers. Solving these challenges takes increasingly complex and precise simulations, the processing of tremendous amounts of data, or training and running sophisticated deep learning networks. These workloads also require accelerating data centers to meet the growing demand for exponential computing.

NVIDIA® Tesla® is the world’s leading platform for the accelerated data center, deployed by the largest supercomputing centers and enterprises. It enables breakthrough performance with fewer, more powerful servers, resulting in faster scientific discoveries and insights while saving money.

NVIDIA Tesla is also the world’s fastest, most efficient data center platform for inference. Tesla provides the optimal inference solution—combining the highest throughput, best efficiency, and best flexibility to power AI-driven experiences.

With over 550 HPC applications GPU-optimized in a broad range of domains, including 15 of the top 15 HPC applications, and all deep learning frameworks, every modern data center can save money with the Tesla platform.

Given the increasingly broad spectrum of data center applications, NVIDIA has gone to great lengths to provide you with the data center products most appropriate for you. As such, the NVIDIA Tesla data center platform features products to account for virtually every data center need, including:

NVIDIA Tesla V100 for NVIDIA® NVLink™

NVIDIA Tesla V100 for PCIe

NVIDIA Tesla P4

NVIDIA Tesla P40

Tesla V100 GPU

At the 2018 GPU Technology Conference (GTC18), it was announced that the memory capacity of the NVIDIA® Tesla® V100 GPU – widely adopted by the world’s leading researchers – was doubled to handle the most memory-intensive deep learning and high performance computing workloads.

Now equipped with 32GB of memory, Tesla V100 GPUs will help data scientists train deeper and larger deep learning models that are more accurate than ever. They can also improve the performance of memory-constrained HPC applications by up to 50 percent compared with the previous 16GB version.

NVIDIA Tesla V100 for NVLink

NVIDIA Tesla V100 for PCIe

NVIDIA Tesla P4

The Tesla P4 is powered by the NVIDIA Pascal™ architecture and purpose-built to boost efficiency for scale-out servers running deep learning workloads, enabling smart responsive AI-based services. It reduces inference latency by 15X in any hyperscale infrastructure and provides a remarkable 60X better energy efficiency than traditional CPUs. This unlocks a new wave of AI services previous impossible due to latency limitations.

NVIDIA Tesla P40

The NVIDIA Tesla P40 is purpose-built to deliver maximum throughput for deep learning deployment. With 47 TOPS of inference performance and INT8 operations per GPU, a single server with 8 Tesla P40s delivers the performance of over 140 traditional CPU servers. As models increase in accuracy and complexity, CPUs are no longer capable of delivering interactive user experience. The Tesla P40 delivers over 30X lower latency than a CPU for real-time responsiveness in even the most complex models. Plus, the Tesla P40 offers great inference performance, INT8 precision and 24GB of onboard memory for an outstanding user experience.

The Accelerated Data Center: Boost Throughput While Lowering Costs

NVIDIA HGX-2

From autonomous vehicles to global climate simulations, new challenges are emerging that demand enormous computing resources to solve. NVIDIA HGX-2 is designed for multi-precision computing to provide a single flexible and powerful platform to solve these massive challenges.

Enables “The World’s Largest GPU.” Accelerated by 16 NVIDIA® Tesla® V100 GPUs and NVIDIA NVSwitch™, HGX-2 has the unprecedented compute power, bandwidth, and memory topology to train these models faster and more efficiently. The 16 Tesla V100 GPUs work as a single unified 2-petaFLOP accelerator with half a terabyte (TB) of total GPU memory, allowing it to handle the most computationally intensive workloads and enable “the world’s largest GPU.”

The Highest-Performing HPC Supernode. HPC applications require strong server nodes with the computing power to perform a massive number of calculations per second. Increasing the compute density of each node dramatically reduces the number of servers required, resulting in huge savings in cost, power, and space consumed in the data center.

NVSwitch for Full Bandwidth Computing. NVSwitch enables every GPU to communicate with every other GPU at full bandwidth of 2.4TB/sec to solve the largest of AI and HPC problems. To learn more about HGX-2, download the NVIDIA HGX-2 Data Sheet.

GPU Cloud Computing.Cloud computing has revolutionized every industry by democratizing the data center and completely changing the way businesses operate. However, to fully pull insight from that data they need the right HPC solution and NVIDIA is partnered with every major cloud service provider.

Design & Pro Visualization

Architecture, Engineering & Construction. NVIDIA plays a key role in the architecture, engineering, and construction (AEC) industries. GPUs are now a part of everything from building design and digital construction rehearsals, to powering autonomous vehicles on construction sites and deep learning enabled on-site safety compliance monitoring.

Manufacturing. From AI and virtual reality to physically based rendering, graphics virtualization, and real-time engineering simulation, traditional product development workflows are being disrupted — empowering manufacturers to radically improve how design teams collaborate and how products are designed and sold.

Leading-edge technologies can radically transform the product development process while reducing costs and speed time to market. Those technologies include:

For 10 consecutive years through 2018, every film nominated for Best Visual Effects at the Academy Awards was created using NVIDIA Quadro GPUs. One of the latest on that long list is War for the Planet of the Apes; excerpt above. (Courtesy of Twentieth Century Fox.)

Real-Time Ray Tracing Realized

Ray tracing is the definitive solution for lifelike lighting, reflections, and shadows, offering a level of realism far beyond what is possible using traditional rendering techniques. Turing is the first GPU capable of rendering real-time ray tracing.

Metro Exodus from 4A Games is the first game using NVIDA RTX ray tracing technology to render high-quality real-time global illumination, variable-rate shading and texture-space shading, and multi-view rendering. To see the stunning impact of RTX from actual Metro Exodus game footage, click here.

Simulating the path of a single light ray as it would be absorbed or reflected by various objects in the image, ray tracing is a technique for presenting three-dimensional (3D) images on a two-dimensional (2D) display by tracing a path of light through pixels on an image plane. In order to bring RTX to fruition, NVIDIA developed new graphical compute subsystems inside their GPUs called “RT Cores” which spur the ray tracing process.

Integrating the Power and Performance of Tensor Cores

To heighten the rendering quality of RTX, NVIDIA went one step better by integrating Tensor Cores – initially produced for deep learning – into the new RTX boards. The result is an accelerated, more efficient rendering process that leverages AI-fueled techniques like “denoising” and “inpainting.”

GeForce RTX graphics cards are also the world’s first graphics cards to feature GDDR6 memory, a new DisplayPort 1.4 output that can drive up to 8K HDR at 60Hz on future-generation monitors with a single cable, and a VirtualLink USB Type-C output for next-generation Virtual Reality headsets.

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